3,756 research outputs found
Internal Model Control (IMC) - Neural Network (NN) Gain Scheduling Untuk Pengendalian Kolom Distilasi
This research is develop the alternative control algorithm using Internal Model Control - Neural Network Gain Scheduling (IMC-NNGS) to control mole fraction of methanol-water distillation column. Distillation column with L-V control strategy has pairing Xd-L and Xb-Qr. IMC performances depend on only ? tuning value or filter time constant. With ? tuning value manipulating IMC could be nonlinear control, where ? tuning value is outputs of NN that had been trained by using error variable, process variable, manipulated variable, and set point variable from plant. Gain scheduling using NN could be increase control system performance and product quality. The best IAE changing value shown at mole fraction feed increase. There are IAE equal with 0,234799 for IMC and IAE equal with 0, 00042 for IMC-NNGS. In other word IMCGS has IAE 559 times better than IMC. Beside that IMC-NNGS has faster response, offset free and robust to overcome set-point and disturbance changes
Realizability and Internal Model Control on Networks
It is proved that network realizability of controllers can be enforced
without conservatism using convex constraints on the closed loop transfer
function. Once a network realizable closed loop transfer matrix has been found,
a corresponding controller can be implemented using a network structured
version of Internal Model Control.Comment: 3 page
Anti-Windup Design for Internal Model Control
This paper considers linear control design for systems with input magnitude saturation. A general anti-windup scheme which optimizes nonlinear performance, applicable to MIMO systems, is developed. Several examples, including an ill-conditioned plant, show that the scheme provides graceful degradation of performance. The attractive features of this scheme are its simplicity and effectiveness
Internal model control
Synthesis of automatic control system aims to do the calculation,
which is the ultimate goal of finding a rational system structure and
establish the optimal values of the parameters of its individual parts.
In energy automatic control system is used to restore normal
operation after emergency situations or for maintaining certain defined
parameters of the system
PERANCANGAN KONTROLER INTERNAL MODEL CONTROLPADA KOLOM DISTILASI Turnitin Cover Nilai
eprints.undip.ac.id/7181
Depth of anesthesia control using internal model control techniques
The major difficulty in the design of closed-loop control during anaesthesia is the inherent patient variability due to differences in demographic and drug tolerance. These
discrepancies are translated into the pharmacokinetics (PK),
and pharmacodynamics (PD). These uncertainties may affect
the stability of the closed loop control system. This paper aims at developing predictive controllers using Internal Model Control technique. This study develops patient dose-response models and to provide an adequate drug administration regimen for the anaesthesia to avoid under or over dosing of the patients. The controllers are designed to compensate for patients inherent drug response variability, to achieve the best output disturbance rejection, and to maintain optimal set point response. The results are evaluated compared with traditional PID controller and the performance is confirmed in our
simulation
Anisochronic Internal Model Control Design
The features of internal model control (IMC) design based on the first order anisochronic model are investigated in this paper. The structure of the anisochronic model is chosen in order to fit both the dominant pole and the dominant zero of the system dynamics being approximated. Thanks to its fairly plain structure, the model is suitable for use in IMC design. However, use of the anisochronic model in IMC design may result in so-called neutral dynamics of the closed loop. This phenomenon is studied in this paper via analysing the spectra of the closed loop system
Observer-based offset-free internal model control
A linear feedback control structure is proposed that allows internal model control design principles to be applied to unstable and marginally stable plants. The control structure comprises an observer using an augmented plant model, state estimate feedback and disturbance estimate feedback. Conditions are given for both nominal internal stability and offset-free action even in the case of plant-model mismatch. The Youla parameterization is recovered as a limiting case with reduced order observers. The simple design methodology is illustrated for a marginally stable plant with delay
- …